impact of micro and small business entrepreneurship on ... · cannot pull yourself up by your...

ISSN: 2306-9007 Adeyemi & Lanrewaju (2014)

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www.irmbrjournal.com September 2014

International Review of Management and Business Research Vol. 3 Issue.3

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Impact of Micro and Small Business Entrepreneurship on

Poverty Reduction in Ibadan Metropolis, South Western

Nigeria

ADEBAYO, NATHANIEL ADEYEMI Department of Business Administration and Management Studies,

The Polytechnic, Ibadan, Nigeria,

Email: [email protected]

Tel: +2348060597810

NASSAR, MOSHOOD LANREWAJU Department of Management and Accounting Obafemi

Awolowo University, Ile Ife, Nigeria.

Abstract

The main objective of this study was to assess impact of Micro and Small business entrepreneurship on

poverty reduction in Ibadan metropolis, South Western Nigeria. The study population was drawn from a

register of relevant trade associations and published government documents, which yieded a total of 383

enterprises. The study used proportional sampling method. The main Statistical tool was the

Counterfactual or Difference-in-Difference model of impact assessment. With exp (β3) = 1.385, the

empirical results indicated that the odds of individuals in micro and small business entrepreneurship in

Ibadan metropolis to earn more than US$1.25 per day increased by 39 %. The study found that the impact

could have been more pronounced but for some socio-economic, infrastructural and management

challenges. Study recommends strengthening of youth entrepreneurship, increased publicity of government

Business Development and Support Services, liberalization of access to and usage of business premises,

reduction in cost of production, improvement of infrastructural facilities among others.

Key Words: Entrepreneurship, Micro and Small Enterprises, Counterfactual Model, Poverty Reduction,

Nigeria, Informal Business Sector.

Introduction

With a population of 140 million, Nigeria is recognised as the most populous country in Africa, accounting

for 47% of West Africa‟s population (World Bank 2007). Although an oil-rich country, a significant

population of Nigeria lives in poverty. Handley, Higgins and Bhavna (2009) noted that approximately 70

million people in the country, live on less than US$1/day [World Bank and Department for International

Development (DFID), 2005], 54% of Nigerians live below the poverty line United Nations Development

Programme (UNDP 2006) and over one-third live in extreme poverty (i.e. those who cannot afford 2900

calories per day) (UNDP, 2006). The country‟s poverty situation has grown worse. According to National

Bureau of Statistics (NBS 2012) by 2010 the number of people in poverty moved to 112.5 million. With

this, 69% of the population lived below the poverty line.

There are suggestions from a number of contemporary studies that implicate unemployment in persistence

poverty (Sanders, 2002; Park, Wang and Wu, 2002). Since unemployment has also been identified as both

a driver and maintainer of poverty in Nigeria (Handley, et al. 2009; Meagher and Yunusa, 1996), it is

instructive to highlight trends in unemployment in Nigeria over the years. This may help appreciate the

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reason for persistence poverty in Nigeria. Unemployment in the country has been on consistent rise for ten

years between 2002 and 2011. It only dropped from 13.4 per cent in 2004 and to 11.9 per cent in 2005. But

from 2006, it has been on the ascendancy again, moving from 12.3 per cent in that year to 23.9 per cent in

2011 (NBS 2010; NBS 2011).

The task of reducing poverty in Nigeria has been herculean making the country to oscillate among several

programmes. In the pre-Structural Adjustment Programme era, the country experimented with not less than

18 poverty reduction programmes. Ogwumike (2002), citing Central Bank of Nigeria (CBN 1998) observed

that these programmes could not be sustained “due to lack of political will and commitment, policy

instability and insufficient involvement of the beneficiaries of the programmes”. Between 1986, when the

Structural Adjustment Programme came afloat and 2012, not less than seven new poverty reduction

programmes have been mainstreamed in Nigeria. Out of these, four can be said to have entrepreneurial

flavour. It can therefore be said that entrepreneurship approach to poverty reduction in Nigeria is a latter-

day development. In sharp contrast to the failure of other global attempts at poverty reduction, there is now

a plethora of studies orchestrating entrepreneurship as a viable route to poverty reduction.

Statement of the Problem

The position that entrepreneurship is a bulwark against poor economic growth, poverty, frustration and

social exclusion appears to be getting widely accepted in most countries across the world. This has resulted

in a massive change towards entrepreneurship and a movement by the Third World countries from public

sector dominated economies to entrepreneurial economies. Nigeria is a quintessential indicator of this

(Magbagbeola, 1996; Chemonics International Inc., 2006).

It is paradoxical however that contrary to the position that entrepreneurship is a panacea for poverty, there

is an increasing number of „the working poor‟, being dominated by entrepreneurs and the self-employed.

For such people, the unpalatable consequences of poverty still abate. Thus many micro and small business

entrepreneurs still experience malnutrition, engage in child labour, lack access to good health care system

and hence suffer sicknesses. Other consequences of poverty which manifest also among „the working

poor‟ include voicelessness, inter-generational transmission of poverty status, and restricted access to good

education.

The existence of „the working poor‟ in an environment of massive micro and small business

entrepreneurship may be suggestive of poor impact of entrepreneurship on poverty reduction. This postion

is often challenged by SMEs Advocates. Consequently there is need for empirical studies to establish the

correct postion. As a result, this study was directed at the following research questions;

Does micro and small business entrepreneurship significantly reduce poverty?

What factors (if any) inhibit optimization of micro and small busness enterprises as effective

agents of poverty reduction?

Literature Review And Conceptual Framework

Literature Review

Reality of Poverty

One of the major socio-economic problems of our time, especially in developing countries is poverty.

Most other socio-economic problems would almost be completely solved, if the problem of poverty is

successfully addressed. Islam (2004) reaffirmed this position, when he said;



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If one were to cite one problem which poses a challenge for world leaders development practitioners (at

the global as well as national levels), and policy makers alike, it is the stubborn persistence of poverty in

many parts of the world. It is only in countries of East and South East Asia (ESEA), that real success in

poverty reduction has been achieved, although that achievement also looked rather fragile during the

economic crisis of the late 1990s.

Lending credence to the same observations Osmani (2003) pointed out that in the past the growth of

national income was taken to be the explicit objective of economic development. More recently, poverty

reduction has come to be accepted as the explicit objective.

Film and Poverty Tourism are aspects of „Poortainment‟ which are now being used to draw attention to the

graphic reality of poverty. „Poortainment‟ is the coming together of Poverty and Entertainment (Karnani

2011). According to Karnani (2011), “poverty in its gritty detail, filthy grime and revolting brutality can be

seen in the film „Slumdog Millionaire‟ “. The film creates the impression that the poor can bootstrap

themselves out of poverty. This has been described as an illusion. According to Hanlon et al. (2010) “You

cannot pull yourself up by your bootstraps if you have no boots.” This study takes the issue beyond illusion

in Hanlon et al. (2010) by focusing on the poor who have „ boots‟ ( i.e. self employment) and assessing if

they have been able to „ bootstrap themselves out of poverty‟.

It is clear from these views that poverty reduction has come to occupy the centre-stage in development

discourse. That its stubborn nature has led to renewed attention and more vigorous pursuit of its reduction

is a reality. This may be the reason for making it the number one issue of the Millennium Development

Goals by the United Nations.

Definitions of Poverty

„Poverty‟ has been variously defined over the years. Economic Development and Development Studies

literature is replete with several definitions of poverty. The fact that, for a long time, there was no

unanimity on the meaning of poverty is a pointer to the problematic nature of the term. Presented in this

section is a review of some of the definitions of the term. This is done in a bid to have a working definition

for this research.

Onibokun and Kumuyi (1996) defined poverty as “a depravation of entitlement through lack of access to

economic and social resources, as well as to political participation and consultation”. Osmani (2003)

preferred a description of poverty as “basic capability failures”, rather than just “low income” as is

commonly believed. According to Osmani (2003), the “failures are such as the capabilities to be free from

hunger, to live a healthy and active life and so on”. From the foregoing, it is clear that poverty is

multidimensional. As a result one cannot agree enough with a former Secretary-General of the United

Nations Organisation, quoted by Onibokun and Kumuyi (1996). According to him, “poverty manifests

itself in the sphere of economics as deprivation, in politics as marginalisation, in sociological issues as

discrimination, in culture as ruthlessness and in ecology as vulnerability”.

Weiser (2011), citing the World Bank (2011) defined poverty as pronounced deprivation in wellbeing and

comprises many dimensions. It includes low income and inability to acquire the basic goods and services

necessary for survival with dignity. Poverty also encompasses low levels of health and education, poor

access to clean water and sanitation, inadequate physical security, lack of voice and insufficient capacity

and opportunity to better one’s life.

Of all the definitions of poverty reviewed here the World Bank (2011) is the most appealing for a number

of reasons. Firstly, it captures adequately the multi-dimensional nature of poverty. Secondly, it highlights

consequences of poverty, with most being amenable to measurement. Finally, it stresses lack of income as

the underlying factor of poverty.



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While the various dimensions of poverty may reinforce one another, income poverty appears to be at the

root of most dimensions of poverty. It is in the light of this that Micro and Small Business Entrepreneurship

require attention particularly in terms of its income-generating capacity. It is also for the same reason that

this study focuses on income poverty.

Theories of Poverty

Ownership of factors of production has been identified by Akeredolu-Ale (1975) as the basis for

propounding a theory of poverty. This is because it is a major determinant of the structure of inter-personal

and inter-group differentials in wealth and income. On the basis of this, four theories of poverty have been

propounded; the Necessity Theory, the Individual-Attributes Theory, the Natural-circumstantial Theory and

the Power Theory.

Necessity theory has three variants; the functionalist, the evolutionist and the capitalist entrepreneurial.

The functionalist variant is based on the belief that specialization leads to efficiency. Those who perform

specialist functions are therefore better rewarded than others, and are better placed in higher economic and

social hierarchies. The evolutionist variant holds that the poor in the society arise spontaneously w

ith inequality and poverty acting as eliminators of the least fit. The third is the capitalist entrepreneurial

variant. This argues that crude exploitation constitutes a major factor in the emergence of the poor, by

giving impetus to increase in saving and aggressive entrepreneurship on one hand and the impoverisation of

labour on the other.

The Individual-attributes theory reacts on the view that the poor in the society are the architects of their

own conditions. According to this theory, the position of an individual in the income and wealth

continuum is dependent on the individual‟s motivation, aptitudes and ability.

The Natural-circumstantial theories have more to do with causes of poverty. According to these theories,

explanatory variables responsible for poverty include geographical location and natural endowment of the

individuals‟ environment, unemployment, old age etc.

The Power theory is predicated on the view that the structure of political power is a major determinant of

the extent and distribution of poverty. This theory has empirical validity in Nigeria‟s situation of a few

hijacking power and organizing the economic system to suit their own interests. It has however been

asserted that the “extent of success of the exploiting class will depend on the revolutionary consciousness

of the subject or oppressed class; on their organizational capacity to resist exploitation and over-throw the

oppressive property system” (Umianikogbo, 1997).

Tella (1999) has however added two additional theories/concepts to the earlier ones in Akeredolu-Ale

(1975). These are the Corruption Theory and Element-of-Luck Theory. Corruption theory postulates that

poverty is rooted in corruption. When the underlying motive of seeking political power is unfettered desire

for material acquisition that will not only last the life time of an individual but also sustain the family after

him, corruption would become manifest. Such material acquisition which is at the expense of the populace

deprives the society the needed resources for poverty reduction. The longer the individuals concerned stay

in power or corridors of power, the more public property including funds, they acquire. Corruption in this

context is therefore seen a driver of poverty.

In the Element-of-Luck theory, poverty is hinged on the accident of birth of the poor. According to Tella

(1999) when people are lucky to be borne into societies that cherish hard work, honesty, self-service, good

values and pride, upon which the younger generation can build, poverty exists mainly within the context of

individual attributes.



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Micro and Small Business Entrepreneurship

Developments in the Theory of MSEs

The main theory of MSE development is often traced to the seminal work by Lewis (1955), which is

commonly referred to as the Labour Surplus Theory. According to this theory, the emergence and

development of MSEs is driven by excess labour supply, which cannot be absorbed by either the public

sector or the large private enterprises of the formal sector, the poor pay and low productivity of these

sectors not withstanding.

In line with this theory, it can be argued that unemployment is a lubricant for MSE growth and

development. When there is high rate of unemployment, MSEs provide a „refuge‟ for those who are not

able to find employment in the formal sector. Green et al. (2006) posit that MSEs are expected to grow in

periods of economic crisis, when formal sector contracts or grows too slowly to absorb the labour force.

However, when formal employment grows, the MSE sector is assumed to contract again and thus

developed an anti-cyclical relationship with the formal economy. The position of Green et al. (2006) on

the anti-cyclical relationship has been strengthened by the trend in MSE development before and after

Structural Adjustment Programme (SAP) in some countries. See for example, Daniels

(1994) and Brand et al. (1995) for Zimbabwe, Meagher and Yunusa (1998) for Nigeria.

Definitions of Micro, Small and Medium Enterprises

Conceptually a business may assume any of the following sizes:

1. Micro-enterprises

2. Small Scale Enterprises

3. Medium Scale Enterprises and

4. Large Scale Enterprises

Over the years, attempts have been made to draw lines of demarcation between one size of business and the

preceding/succeeding ones. This is particularly true of micro-enterprises and small scale enterprises and

between the latter and medium scale enterprises. Effort in this regard has a long history leading to

multiplicity of definitions across and within countries. In actual fact Olabisi et al. (2011) inform that ILO

(2005) in a study identified 50 definitions of MSMEs in 75 different countries.

The multiplicity and lack of consensus in defining micro, small and medium enterprises observed across

countries and among international organisations does not exempt Nigeria. From table 2.3, it can be seen

that various government organisations in Nigeria have given different defintions of these enterprises at

different times. In some cases one organisation had given different definitions at different times. This is

especially the case with Central Bank of Nigeria (CBN) in 1988 and 1993. Another example of this is

Companies and Allied Matters Decree - CAMD (1990) and Companies and Allied Matters Act- CAMA

(2004).

One of the most recent definitions in Nigeria is found in Udechukwu (2003) who reported this as being part

of the outcome of the 13th Meeting of the National Council on Industry (NCI) in Markudi, Benue State, in

July 2001. Based on this:

(a) a micro/cottage Industry is an industry with capital not more than N1.5million including

working capital but excluding cost of land and/or a labour size of not more than 10 workers.

(b) a small-Scale industry is one with total capital employed of over N1.5million but not more than

N50million including working capital but excluding cost of land or a labour size of 11-100

workers.



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(c) a medium-scale Industry: is an industry with a total capital employed of over N50million but

not more than N200million including working capital and a labour size of 101-300 workers.

This research has adopted these definitions of micro, small and medium enterprises (MSMEs) as given by

the National Council on Industry for a number of reasons. Firstly, it is about the most current definition.

Settling for an acceptable definition has a lot to do with time, because of the need for time value of money

in capital specification. Secondly, the defining authority is the highest organ on commerce and industry

matters in Nigeria. Finally, the two prominent parameters in business size classification (capital and

workforce) are included.

Table 1; Various Definitions of Business Size in Nigeira

Source Definition

Owualah (1999) Micro enterprises: Firms with as many as 10 workers, although the

norm is 1or2. Owned by the poor, women, disabled, youths. Typically

family business in the informal sector.

Eigege (1991) Small scale enterprises: Firms with yearly turnover not exceeding US$

3million (China, Hong Kong, Korea).

Federal Ministry of

Commerce and Industry –

1981/83 Guideline to NBCI.

Small business enterprises: Firms with total cost of not more than

N500,000 (excluding land but including working capital)

Central Bank of Nigeria

(CBN) 1988

Small scale enterprises: (Excluding general commerce) investment

(including land and capital) not exceeding N500,000 and/or annual

turnover not exceeding N5million.

Central Bank of Nigeria

(CBN) 1993

Small business enterprises: Firms with total cost, excluding cost of land

but including working capital above N1million but not excluding

N10million.

Companies and Allied

Matters Decree (1990).

Section 376 (2).

Small company: Firm with a value of not more than N1million.

Companies and Allied

Matters Act 2004. Section

351(1).

Small Company: A particular year is one with turnover of not more

than N2million and net assets of not more than N1million.

NERFUND Small business enterprises: Firms with fixed assets plus cost of new

investment not exceeding N10million.

Bankers Committee (Nigeria)

for purpose of Small and

Medium Enterprises Equity

Investment Scheme

(SMEEIS) – 1999.

Small and Medium Enterprises: Firm with a maximum asset base of

N500million (excluding land and working capital).

National Council on Industry

(2001) Udechukwu (2003)

Micro/cottage Enterprises: Firm with capital not more than

N1.5million including working capital but excluding cost of land and/or

labour size of not more than 10 workers.

Small scale enterprises: Firm with total capital of over N1.5million but

not more than N50million including working capital but excluding cost

of land and/or a labour size of 11-100 workers.

Sources: Owualah (1999); Eigege (1991); CBN (1988; 1993); CAMD (1990); CAMA (2004) Demeke et

al. (2006); Udechukwu (2003).

Whereas the two dominant parameters (capital and workforce) are included in the adopted definitions, the

research will stratify the respondent businesses into micro and small business enterprises using the criterion

of workforce. The major reason for this is that it is more objective. Using the capital criterion will require

a sound knowledge of what constitutes business capital and a resolution of whether it is „Start-up Capital‟



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or „Working Capital‟ that should be used. Since most of the potential respondents may lack the ability to

distinguish between the one and the other, the use of workforce, which is less controversial is preferable for

this study.

Empirical Literature

Empirical Studies on Impact of Micro, Small and Medium Enterprises (MSMEs)

In a study of developmental impact of investments in ten small and medium enterprises in the Small

Enterprises Assistant Funds (SEAF) observed that SMEs have the potentials of being a vehicle not only for

growth, but also for poverty reduction. SEAF (2004) has highlighted the results of the study, indicating all

the “ten case studies demonstrate the multiple paths by which these SMEs have affected their

communities”.

The SEAF study reveals among other things that

* The economic impact of investments in SMEs is significant. In specific terms, the study observed

that every dollar invested by SEAF generated an additional ten dollars in local currency.

* The greatest share of benefits from the investments gives to employees, followed by governments.

* Two thirds of total employment in the sampled firms gives to low-skilled workers. This

strengthens the hypothesis that SMEs generate new jobs which are suitable for the poor.

* Employees annual real wage growth can be as high 28% for low-skilled and 34% for high-skilled

workers.

* The enterprises also provide non-salary benefits.

Shrestha (2004) investigated impact of Micro and Small Enterprises, supported by the Micro-Enterprise

Development Programme (MEDEP) on a number of targets, in Nepal. Poverty reduction was in the menu

of the targets focused by the investigation. The study found that “almost every enterprise yields an

interesting case study of successful entrepreneurship strategy and a significant economic and moving

personal transformation of the newly minted entrepreneurs” Shrestha (2004).

According to Shrestha (2004) in Nepal, Micro and Small enterprises have recorded positive impacts with

regard to indicators such as income, local communities, poverty reduction, women empowerment and

micro and macro linkages. Shrestha (2004) found that the poor through micro enterprises achieved

significant increases in income of between 50 percent and 100 percent with an overall average of income

increment of about 50 per cent. The report mentioned that total income before MEDEP intervention was

about $69 per year and after intervention it rose to about $105. In terms of job creation, the study found

micro enterprises creating total employment for about 8, 139 persons i.e. an average of about 1.3 persons

per entrepreneur. Using basic needs approach to evaluating poverty, Shrestha (2004) found that households

that were incapable of meeting these needs before MEDEP intervention, were financially empowered

through micro-entrepreneurship to do so.

Using inequality decomposition techniques, Kimhi (2009) found that a uniform increase in entrepreneurial

income reduces per capita household income inequality in Southern Ethiopia. Consequently, the study

concluded, “that encouraging rural entrepreneurship may be favourable for both income growth and income

distribution.” Beck, Demirgue-Kunt, Levine (2003) evaluated the impact of SMEs on growth and poverty

using cross-country growth regression framework. Their study in this regard concluded that there was no

robust relationship between the size of the SME sector and the incidence of poverty, or income per capita

or its growth rate.

Two other studies that strengthen the poverty-reduction potentials of micro, small and medium enterprise

are Demeke et al. (2006) and Rahman and Islam (2003). Findings from these studies showcase how

employment (self – or wage) can lead to poverty reduction, and even wealth creation.



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The significant role played in the economy of Ethiopia by MSEs (Micro & Small Scale Enterprises) has

been pointed in Demeke et al. (2006). According to them SMEs, provide income and employment for

significant proportions of workers in rural and urban areas by producing basic goods and services for

rapidly growing populations… contributing over 99% of all enterprises, over 60% of private sector

employment and about 30% or 80 of exports.

Rahman and Islam (2003) in doing a comparative analysis of which of the two routes to poverty reduction

(wage – employment and self-employment) was more effective in Bangladesh found that:

i) Wage workers are more prone to poverty than the self-employed and that is reflected in the

lower hourly earnings of the former.

ii) The average returns from self-employment is much lower for the poor than the non-poor

group, implying that the nature of self-employment in which the poor are engaged is different

from the non-poor and

iii) Education is an important factor in determining the probability of a household being poor.

The findings of Rahman and Islam (2003) indicate that self-employment can fast track poverty reduction

than wage employment. In a country like Nigeria, where there was a strong attachment to wage

employment and a lethargy for self-employment, these findings are instructive ot only for combating

unemployment but also for poverty reduction.

Conceptual Framework

Relying on OECD/EUROSTAT Entrepreneurship framework in Ahmad and Seymour (2008), we propose a

model, which links Lewis Labour Surplus Theory and labour market dynamics with entrepreneurship as a

window of possible exit from poverty. This conceptual framework is presented as figure 1. In this

conceptual framework Lewis Labour Surplus Theory and Labour Market Dynamics constitute the

antecedent variables. Determinants of nature and motivation for entrepreneurship constitute intervening

variables. Independent variables are made up of key factors in business performance while the depedent or

outcome variable which captures impact of micro and small business entrepreneurship is poverty reduction

through job creation.

Fig. 1: Integrated Framework of Poverty-Entrepreneurship Linkage.

Source: Designed by the Author

In labour

force

Outside

of labour

force

Entrepre-

neurship

Wage

Employment

Determinants

*Necessity

*Opportunity

Impact Performance

* Socio-

economic

*Demographic

* Perception

Job

creation

Poverty

Reduction

Labour

Surplus

Theory

and

Income

Poverty

Antecedent

Variables

Intervening

Variables

Independent

Variables

Dependent

Variable/Outcome

Labiur Market

Dynamics Entrepreneurship Framework



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Research Methodology

Area of Study

The area of study is Ibadan metropolis in South Western Nigeria. Although Nigeria has 36 states and six

geopolitical zones, the choice of South Western zone was informed by the fact that South West is the

commercial hub of Nigeria and is recognized as the zone with the lowest poverty indices (NBS, 2012). It

is necessary to study the zone as a model and see the extent to which micro and small business

entrepreneurship has contributed to these low poverty indices.

Outside Lagos, which was Nigeria‟s Federal Capital before Abuja, Oyo State, which has Ibadan Metropolis

as capital, has the highest concentration of micro and small business enterprises in South Western Nigeria.

This is 3.03% compared to Ekiti (2.44%), Ogun (2.73%), Osun (2.79%) and Ondo (2.84%). With micro

and small business enterprises being the subject – matter of this research Oyo State is therefore

quintessential.

Ibadan metropolis itself is made up of five local governments and has long been recognized as the most

indigenous urban centre in Africa, South of Sahara Adeniji-Soji (1996). Ibadan metropolis plays host to

almost all tribes in Nigeria and certainly all the major ones. As a result it is a miniature of Nigeria,

providing possibility of making findings from this study applicable to the whole country.

The economic, social, political and demographic structure of Ibadan Metropolis also provides a good

setting for the study of the impact of micro and small scale entrepreneurship on poverty reduction. Ibadan

is the third largest metropolitan area by the 2006 population census in Nigeria after Lagos and Kano. It is

also the largest metropolitan geographical area. Outside Lagos, Ibadan is the largest metropolitan city of

South Western Nigeria with a population of 1,338,649 (National Population Commission, 2006). From the

2006 population exercise, Ibadan North East is the biggest of the five local governments in the metropolis,

accounting for 24.7 per cent. It is followed by Ibadan North (22.9%), Ibadan South West (21.1%) with

Ibadan North West (11.4%) being the smallest.

Study Population

Micro and Small business enterprises in Ibadan metropolis constitute the study population for this research.

Most of these enterprises are located in the informal sector of the economy. Since the informal sector is

“invisible non- structured” Magbagbeola)1996) determining accurate study population is difficult.

For the purpose of this research however, the study population was drawn from list of members of the

National Association of Small Scale Industrialists (NASSI), registers of trade associations that are not

members of NASSI and the 2010 edition of Industrial Directory. The study population going by these

sources was 383.

Sampling Methods

This research used proportional stratified sampling method. The study population was divided into strata,

first in term of size (ie Micro and Small Enterprises using the criteria in Udechukwu (2003), second in

terms of sectors and third in terms of entrepreneurial motivation (necessity and opportunity). The sample

frame was the proportion of each stratum in the study population. For good representativeness and

generalization of results, a sample frame of 80% of the study population was used. The choice of

proportional stratified sampling method was informed by its potential advantages. First is that it promotes

precision. Secondly, proportional stratified sampling is adiministraively convenient. Research assistants

were trained to deal with respondents in line with the peculiarities of each stratum. Finally, this method

ensures better coverage of the study population than stratified random sampling.



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Sources of Data

The data for this study came mainly from primary sources. They (data) were collected through a

questionnaire designed and administered on the study sample. This was complemented with guided

interview by the research assistants where necessary. The guided interview largely enabled the research

assistants explain some key terms in the Questionnaire. In order to arrive at reasonable figures of income

earned, a dairy was opined for the purpose recording daily earning of the respondents. This was done for a

period of three months – September to November 2012. The mean of these figures has been used for each

of the respondents.

Structure of Questionnaire

The questionnaire was divided into four sections apart from the introduction.

- Section A: Bio-data on the respondents. It should be stated that in order to encourage quick and

honest responses, the rule of anonymity is observed.

- Section B: Business history and operation.

- Section C: Entrepreneurial Characteristics.

- Section D: Socio-Economic and Demographic Characteristics.

-

Administration of the Research Instrument

The study used The Spearman-Brown and Cronbach alpha for realibility test. This was preferred because it

captures full scale realibility rather than split half reliability and yielded a value of 0.73. This implies that

the instrument of data collection was reliable in stability, dependability and predictability. Cronbach Alpha

(α) applied for validity test yielded a value of 0.71. This indicates a highly valid instrument. The study used

trained Research Assistants to distribute, interview and retrieve the questionnaires. Data collection through

Questionnaire was complemented with Guided Interview.

Method of Data Analysis

This research depended heavily on some related works that had been done on poverty impacts of Small

Enterprises Initiatives (Nexus Associates, 2002: Oldsman and Hallberg, 2003), characterisation of Micro

and Small business entrepreneurs (Bhola et al. 2006, Wagner, 2005), on entrepreneurial earnings and

impact on poverty (Wagner, 2003; Block and Sandner, 2005; Block and Koellinger, 2006; Block and

Wagner, 2006) Data were analysed using Statistical Package for Social Sciences (SPSS version 17).

Modelling for Assessment of Poverty Impact of Micro and Small Business Enterprises

The model of poverty impact of micro and small business entrepreneurship used in this study is highly

dependent on Nexus Associates (2002) and Oldsman and Hallberg (2003) and originally requires six steps

to be taken. Over the years measuring impact of policy has been confused with evaluating effects of

policies. The fundamental tenet of impact assessment is the need to compare the observed situation (ie post

intervention) with what was the case was before intervention (pre-intervention). This is what is called the

Counterfactual. The difference between the two states is the real impact and explains why it is also called

Difference-in-Difference model. In the context of this research, impact of micro and small business

entrepreneurship on poverty reduction is a comparison of the poverty status of the entrepreneurs before and

after engagement in business. It is in line with this methodology that the model in explicit term is stated as;

PoV = βo + β1 EDP + β2BAGE + β3 (EDP * BAGE) + βj Xj + e

Here exp (β3) is the predictor of impact.



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In this model the dependent variable (POVERTY) is dichotomous, hence the need to estimate it using logit

regression. It was scored „1‟ if earning of an entrepreneur was above the poverty line of ($1.25) and „0‟ if

otherwise. This absolute poverty line was converted to local currency using the average official exchange

rate of N150 (2011) to a US dollar.

- EDP = dichotomous variable on whether a business is an entrepreneur‟s only source of income or

not. It equals „1‟ if it is the only source and „0‟ if there are others.

- BAGE = the age of the business in question.

- Xj = vector of other variables believed to affect poverty rate. Such variables for this study are

listed on table 3.

Table 3: Variables for Logistic Estimates for Socio-Economic and Demographic factors affecting Micro

and Small Business Entrepreneurs‟ Poverty.

Variable Variables Description A Priori Expectation

Dependent Variable

POV Poverty line of $1.25 at 2011 official exchange rate

= 1 if income is more than it

= 0 if income is less it.

Explanatory Variables

HSIZE Size of entrepreneur‟s household +ve

AGEH Age of the entrepreneur -ve

HOUT Type of housing

= 1 If entrepreneur‟s household resides in block of

flats.

= 0 If lower than flats

-ve

EDUC Household education level

No education for a household member=0

Education up to junior secondary level=5

Education up to senior secondary school level=10

Education up to /university

/polytechnic/college=15

Index= total points/household size

-ve

PARR Participation rate;

No of workers in the household/No of adults

-ve

HOHC Household Health Care

= 1, If entrepreneur‟s uses private hospitals

= 0, If otherwise

-ve

BUPO Business Property Ownership

= 1, If entrepreneur has landed property

= 0, If otherwise.

-ve

DEPR Dependency ratio

‹18yrs+›60yrs/ No of others

+ve

Source: Adapted from Chaudhry et al. (2009).

There are six steps required in using the Counterfactual Model.

Step 1: Selection of Poverty Indicator:

In this research $1.25 per day absolute poverty line was. One major reason for this is the World Bank

having revisted the dollar-per-day measure, had since 2005 established that $1.25 per day is more realistic

in measuring extreme poverty. This according to Chen and Ravallion (2008) is the updated international

poverty line. Secondly and arising from the first reason is the fact that underestimation of poverty situation



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engendered by the use of $1 per day is avoided. Thirdly according to Haughton and Khandker (2009)

“absolute poverty line is essential if one is trying to judge the effect of antipoverty policies overtime or

estimate impact of a project (for example micro credit) on poverty”. Since this study is on impact of micro

and small business entrepreneurship on poverty reduction, it is only appropriate that absolute poverty line is

used.

Step 2: Selection of Time Period

For this study the number of years within which is the micro and small business enterprises have been in

existence is used.

Step 3: Obtaining Data

Data used were primary in nature and therefore questionnaire was employed as an instrument of collection.

This was complemented by guided interview and use of diary. The latter was to a fair knowledge of

earnings of the respondents.

Step 4: Construction of Control Group

In this study, the treatment group consisted of those micro and small business entrepreneurs whose only

sources of income were the businesses under study. They were scored „1‟. The control group on the hand

was made up of those who had other sources of income apart from the businesses in question. They were

scored „0‟.

Step 5: Estimate of Poverty Impact

As mentioned earlier β3 is the predictor in the model. It estimates poverty impact.

Step 6; Model Interpretation

The coefficient β3 tells how the log-odds in favour of escaping poverty (defined as earnings above the

poverty rate) change since being in entrepreneurship.

Taking the antilog of β3 (the odds ratio) tells us how the odds have changed for the entrepreneurs, since

being in business. E.g. exp (β3) = 1.18 is interpreted as meaning that the odds for the entrepreneurs to earn

more than the defined poverty rate (e.g. US$1.25 per day) increased by 18% more than the period before

business.

Results and Discussion

Whereas the study aimed at a sample of 90% of the study population (383), the number of questionnaire

retrieved and valid for analysis was less. 345 copies of the questionnaire were distributed, 15 copies could

not be retrieved while 24 copies were not properly filled, making them invalid and unusable. In all a total

of 306 copies were both properly filled and returned. In other words, the sample for this study is 80%.

Frequency and Percentage Distribution of Respondents by Socio-economic Characteristics and

Business Location

The distribution of respondents by gender, age, educational status and location of business by local

government is shown in table 4.1. From this table, there were more male (68.6%) in micro and small

business entrepreneurship than female (31.4%). This is expected as men are usually the dominant bread

winners of many households. The data also revealed that no foreigner was found in micro and small



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business entrepreneurship in Ibadan metropolis. The business units under study are principally of informal

sector and as a result having 100% Nigerians in them is also expected.

Table 4.1 also presents the age structure of the sampled micro and small business entrepreneurs. From this

table micro and small business entrepreneurs between 18 and 35 years were 49.3%, closely followed by

those between 36 and 60 years (41.8%). The rest consisted of those below 18 years (8.5%) and those above

60 years (0.3%). From this sample, micro and small business entrepreneurs in Ibadan metropolis were

predominantly young. This is followed by the adult population who constituted 41.8%. Since the active

labour force is made up of those between 18 and 60 years, whose combined population in this study is 279

(or 91.2%) the study is made richer. This is because most of the respondents (91.2%) belong to the age

group, whose employment should be a major source of concern.

About one third (36%) of the micro and small business entrepreneurs had primary and secondary education.

This is followed by those with early tertiary education (ND/NCE holders), (33.6%). Another 26.8% held

Higher National Diploma (HND) degrees. The remaining 3.6% of the sample held Post Graduate

qualifications. In essence 64% of the respondents had 3.6% of tertiary education, while 36% had primary

and secondary education.

From this table Ibadan North Local Government had the highest respondents of 30%, followed by Ibadan

North West 21%, Ibadan South East 19%, Ibadan South West 17% in that order. Ibadan North East had

lowest number of respondents of 13%.

Table 4.1 Frequency and Percentage Distribution of Respondents by their Socio-economic Characteristics,

Business Location and Nature of Business

Socio-economic

characteristics

Frequency Percentage Cumulative

Gender

Female 96 31.4 31.4

Male 210 68.6 100.0

Nationality

Nigerian 306 100.0 100.0

Foreigners 0 0.0 100.0

Age of Entrepreneurs

Under 18 years 26 8.5 8.5

18 – 35 years 151 49.4 57.9

36 – 60 years 128 41.8 99.7

Above 60 years 1 0.3 100.0

Educational status

Primary 47 15.4 15.4

Post primary 63 20.6 36.0

Tertiary 196 64.0 100.0

Location

IBN 92 30 30

IBNE 40 13 43

IBNW 63 21 64

IBSE 58 19 83

IBSW 53 17 100

Source: Field Survey (2012)



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Frequency and Percentage Distribution of Respondents by Nature and Characteristics of Business

Table 4.2 also presents respondents by type of business. Manufacturing enterprises in the context of this

research include businesses in carpentry, bakery, cake-making, pure water production, metal fabrication,

welding, furniture making etc. Enterprises in services on the other hand include sawmilling,

motor/motorcycle repair, barbing, hairdressing, proprietorship of schools etc. Enterprises captured under

distribution are not difficult to identify. They include all businesses that are involved in hawking, trading,

sale and marketing.

From table 4.2, 41.5% of the respondents were engaged in distribution, while those in services were 31.4%.

Those engaged in manufacturing were 24.8%. 2.3% of the respondents could not however be classified.

Entrepreneurship literature has theoretically established two dominant motives of entering into business;

exploitation of economic opportunity and inability to secure alternative means of livelihood. Those who

engage in the former are called opportunity entrepreneurs while those engaged in the latter are referred to

as necessity entrepreneurs. From table 4.2 about 70.3% of the respondents were into necessity

entrepreneurship while the remaining 29.7 percent were engaged in opportunity entrepreneurship.

Micro and small business entrepreneurs who had been in business for more than ten years were 63/7%..

Those in business for between five and ten years were 32.0%, while micro and small business

entrepreneurs in business for less than five years were 4.3%. Considering the position in this study that a

period of five years should be fairly adequate to begin to feel the impact of entrepreneurship on poverty

reduction, from table 4.26 more than 95 per cent of the sample met this specification.

Enterprises employing between 1 and 10 workers accounted for 87.9 percent of the sample. The remaining

12.1% employed between 11 and 100 workers. Going by the adopted operational definitions of micro and

small enterprises, 87.9% of the sample were micro enterprises while 12.1% were small business

enterprises.

Size of capital is one of the criteria in classifying firms/businesses into micro and small enterprises. In line

with our adopted definitions, which is in conformity with National Council on Industry, any enterprise with

capital of not more than N1.5million is a microenterprise. Businesses with more than N1.5million but not

more than N50million are small business enterprises. Medium business enterprises are firms with total

capital of N50million but not more than N200million.

From table 4.2 the study sample was made up of 258 microenterprises, 45 small business enterprises while

only 3 respondents fell outside our study focus not being in any of the earlier two groups. By implication

using capital criterion, 84.3% of the businesses were microenterprises and 14.7% were small business

enterprises. The remaining 1 per cent was larger than micro and small business enterprises. For reasons

earlier advanced, the study used number of workers rather than size of capital.

From table 4.3, 91.2% of the respondents had no other sources of income except the one under study. The

remaining 8.8% had additional sources of income. Since this study is mainly concerned about impact of the

micro and small business entrepreneurship under study, 91.2 per cent of the sample fell into this group.

Although the number of respondents with experience before business engagement was higher at 50.3%, the

difference is marginal when compared with 49.7% that had no such experience. From table 4.3 therefore

50.3% of the respondents had pre-engagement experience while 49.7% had no experience in the business

field prior to engagement.

A total of 225 out 306 were unemployed after their highest qualifications, while 81 of them did not

experience unemployment. By implication 73.5% were unemployed before entrying into business. 26.5%

did not experience unemployment. Of the respondents who experienced unemployment before engaging in



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business, 41.8% had two-year duration, 26% had one year, 4.6% had three years and 0.3% had four years

experience of unemployment before business engagement. This distribution is also shown on table 4.3.

The implication of this distribution is obvious; that most graduates of Nigeria‟s educational institutions do

not wait too long expecting jobs that would never come. The reality of unemployment and the need to

embrace self-employment now appears to stare most of them in the face.

Table 4.2: Frequency & Percentage Distribution of Respondents by Nature and Characteristics of Business

Nature of Business Frequency Percentage Cumulative

Manufacturing 76 24.8 24.8

Distribution 100 32.7 57.5

Service 130 42.5 100.0

Entrepreneurial Motivation

Opportunity 91 29.7 29.7

Necessity 215 70.3 100.0

Age of Business

< 5 years 13 4.3 4.3

5 – 10 years 98 32.0 36.3

> 10 years 195 63.7 100.0

Number of Workers

1 – 10 280 87.9 87.9

11 – 100 26 12.1 100.0

Size of Start-up Capital

≤ 1,500,000 258 83.3 83.3

1,500,001 – 50,000,000 45 14.7 98.0

> 50,000,000 3 1.0 100.0

Source: Field Survey, 2012

Frequency and Percentage Distribution of Respondents by Streams of Income, Unemployment and Pre-

Engagement Experiences.

Table 4.3 Respondents by Unemployment and Pre-Engagement Experience and Business Outcomes

Number of Sources of Income Frequency Percentage Cumulative

Current business only 279 91.2 91.2

Multiple streams 27 8.8 100.0

Pre-Engagement Experience

No Experience before Business Engagement 152 49.7 49.7

Experience before business Engagement 154 50.3 100.0

Experience in Unemployment

Unemployed after School 225 73.5 73.5

No Unemployment after School 81 26.5 100.0

Duration in Unemployment

0 years 81 26.5 26.5

1 82 26.8 53.5

2 128 41.8 95.1

3 14 4.6 99.7

4 1 0.3 100.0

Influence of Unemployment on Business Start-up

Unemployment prompted Business Start-up 225 73.5 73.5

Unemployment did prompt business start-up 81 26.5 100.0




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From table 4.3, 72.2% of the respondents were pushed into business as a result of fear of unemployment.

The remaining 27.8% started business without due regard for the prevailing high unemployment rate in the

country. This distribution is fairly in alignment with respondents‟ disposition on motivation for

engagement in self-employment. The 27.8% that went into business regardless of the unemployment

situation were pulled into entrepreneurship and hence aligning with opportunity entrepreneurship.

Frequency and Percentage Distribution of Respondents by Household Characteristics

Table 4.4 presents data on the main household characteristics. The standard active labour force age is

between 18 and 60 years. From table 4.4, 64.4% had between 1 and 5 members in this age group, 17.3%

had no member of the household within the age group, and 15.7% had between 6 and 10 members in the

active labour force. Those with more 10 members of household in the threshold were 1.6%.

Conceptually household members who are less than 18 years old are usually of school age. As a result they

are excluded from those in labour force. They however constitute part of the dependents. From table 4.4,

78.8% of the sampled micro and small business entrepreneurs had between 1 and 5 members of the

household in this group. 14.7% had between 6 and 10 in the group. The remaining 6.5% had nobody that

was less than 18 years in the household. Household members who are above 60 years are usually

considered to be out of labour force. They therefore constitute another important segment of dependents.

From table 4.4, 53.3% of the respondents had nobody in this age group, while 46.1% had between 1 and 5

members of the household in the group. The remaining 0.7% had between 6 and 10 members of the

household in the group.

Frequency and Percentage Distribution of Respondents by Other Business Outcomes

Engagement in business may be fun especially for habitual entrepreneurs but for most entrepreneurs

especially micro and business entrepreneurs and including novice entrepreneurs, it is not for fun. Several

outcomes most of which are indices of performance measurement are often expected. Two of these are

income and business property. Income generated by micro and small business enterprises is an important

variable of this study. This is because of the interest of the study in determining the extent to which such

generated income impact on the entrepreneurs‟ poverty reduction. From table 4.5, 48.7% of the respondents

earned less than N5, 500 per month. Those who earned between N5,501 and N10,000 were 34.3%, while

7.5% of the micro and small business entrepreneurs, earned between N10,001 and N20,000. 5.2% of the

respondents earned between N20,001 and N40,000, while 2.6% earned between N40,001 and N50,000.

Micro and small business entrepreneurs who earned above N50, 000 were 1.6% of the study sample.

Table 4.4 Respondents by Household Characteristics

Number of Household’s Active Labour Force Frequency Percentage Cumulative

0 53 17.3 17.3

1 – 5 200 65.4 82.7

6 – 10 48 15.7 98.4

Above 10 5 1.6 100.0

Less 18 years old Household members

0 20 6.5 6.5

1 – 5 241 78.8 85.3

6 – 10 45 14.7 100.0

Above 60 years old Household members

0 163 53.3 53.3

1 – 5 141 46.1 99.4

6 – 10 2 0.6 100.0




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Business property is a constituent of business wealth. Ownership of business property is therefore an

indicator of financial bouyancy of an entrepreneur. It is also an index of business prosperity and positive

signal in poverty reduction.

From table 4.5, 96.7% of the respondents claimed that they were not the owners of the properties on which

their businesses were located, while 3.3% of them asserted that they owned the properties on which their

businesses were located.

Business property is a constituent of business wealth. Ownership of business property is therefore an

indicator of financial bouyancy of an entrepreneur. It is also an index of business prosperity and positive

signal in poverty reduction.

From table 4.5, 96.7% of the respondents claimed that they were not the owners of the properties on which

their businesses were located, while 3.3% of them asserted that they owned the properties on which their

businesses were located.

Table 4.5 Respondents by other Business Outcomes

Frequency Percentage Cumulative

Income Generated by Business per month

≤ 5,500 149 48.7 48.7

5,501 – 10,000 105 34.3 83.0

10,001 – 20,000 23 7.5 90.5

20,001 – 40,000 16 5.2 95.7

40,001 – 50,000 8 2.6 98.3

> 50,000 5 1.7 100.0

Ownership of Business Property

Not owners of

Business Property

296

96.7

96.7

Owners of Business

Property

10

3.3

100.0


Table 4.6 Respondents by Dependency Burden Indices

Size of Household Frequency Percentage Cumulative

1-5 270 88.2 88.2

6 – 10 36 11.8 11.8

Above 10 0 0 100.0

Size of Dependants

0 117 38.2 38.2

1 42 13.7 51.9

2 62 20.3 72.2

3 37 12.1 84.3

4 25 8.2 92.5

5 23 7.5 100.0


Frequency and Percentage Distribution of Respondents by Awareness of Government BDSS, Sources

of Initial Capital and Observed Constraints to Business Performance

Establishment of some agencies, especially by the Federal Government of Nigeria, was to provide largely

business development and support services. The aim is not just to rekindle the entrepreneurial spirit, it is



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also to boost business performance. Such agencies include the National Directorate of Employment

(NDE), National Poverty Eradication Programme (NAPEP) and Small and Medium Enterprises

Development Agency of Nigeria. (SMEDAN).

From table 4.13, 173 of the respondents were aware of the activities of National Directorate on

Employment (NDE). 146 were aware of the existence of National Poverty Eradication Programme

(NAPEP) and 85 had knowledge of the existence of Small and Medium Enterprises Development Agency

of Nigeria (SMEDAN).

Potential sources of business start-up capital especially for enterprises in the informal sector include

personal saving, loans from friends and relations loans from co-operatives and banks (especially

microfinance banks). From table 4.13, loans from friends and relations appear to be the most popular with

175 respondents. It is followed by personal saving (134), loans from co-operative societies (57), loans

from banks (29) and from government agencies like NAPEP, NDE etc.

In an effort to understand what factors might have obstructed desirable performance of micro and small

business enterprises, respondents were asked to select from a list of factors. From table 4.13, the strongest

constraint was capital/business funding, followed by low patronage, high cost of input/wares, lack of

desired manpower, and government policies in that order. Excessive taxation is the least and this is

understandable. Most micro and small business entrepreneurs did not pay tax. In addition some of the

micro and small business entrepreneurs in the study sample (through guided interview) volunteered

information that it was difficult for them to get workers who were honest and committed.

Table 4.13 Distribution of Respondents by Awareness of Government BDSS, Sources of Initial Capital and

Observed Constraints to Business Performance

Frequency Ranking

Awareness of Government BDSS

NDE 173 1

NAPEP 146 2

SMEDAN 85 3

Initial Sources of Capital

Personal Saving 143 2

Loans from friends & Relations 175 1

Loans from Banks 29 4

Loans from Co-op Society 57 3

Loans from Govt. Agencies 9 5

Observed Constraints to Business Performance

Lack of capital/Finance 289 1

Low Patronage 215 2

High cost of Input/Wares 197 3

Government Policies 80 5

Excessive Taxation 30 6

Lack of Desired Manpower 125 4


Impact Assessment

Using the concept of Counterfactual otherwise called Differences-in-Differences method, where

POV=βo + β1 EDP +β2 BAGE + β3 (EDP * BAGE) + βj Xj +e

the logistic regression results are as shown on table 4.14. From these, the coefficient of (EDP *BAGE),

which is the predictor (i.e β3), is significant at 0.05 level. The exp (β3) value is 1.385. The log odds is



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therefore about 39%, implying that the odds for micro and small business entrepreneurs in Ibadan

metropolis to earn more than US$1.25 per day increased by 39%. Consequently the hypothesis that micro

and small business enterprises do not significantly reduce poverty is accepted.

Table 4.14: Logit Regression of Impact of Micro and Small Business Entrepreneurship on Poverty

Reduction

B S.E Weld Df Sig. Exp (β)

EDP -1.668 0.836 3.986 0.646 0.189

BAGE -0.367 0.416 0.778 0.378 0.693

EDP * BAGE 0.326 0.470 4.045 0.044 1.385

Constant 0.274 0.699 0.154 0.695 1.315

a Variable(s) entered on step 1; EDP, BAGE, (EDP * BAGE)

For micro and small business enterpreneurship to reduce poverty by 39% may ordinarily be considered as

relaively good. But when compared with the duration within which the entrepreneurs had been in business

(95.8% had been in business for more than 5 years: table 4.2), the small size of household and the relatively

good participation rate, this may not be significant enough.

Recommendations

It is clear from empirical results of this study that micro and small business entrepreneurship can contribute

significantly in the drive for poverty reduction. Its impact on poverty reduction can be more pronounced

and contribution raised from the marginal level observed in this study, if all stakeholders, especially policy

makers will recognise and implement the following recommendations which have arisen from the findings

of this study.

Firstly, since it has been established from this study that micro and small business entrepreneurship can

help in the poverty reduction drive, government at all levels of administration should put in place

appropriate policies to encourage, stimulate and sustain entrepreneurial spirit, especially in Nigerian

youths.

There are several ways through which this can be done. The recent introduction of Entrepreneurship

Development in all tertiary institutions is a right step in the right direction. This effort should however go

beyond limiting choice of trade to those that are merely available on campus. Skills acquisition under such

programme should follow deliberate systematic and approach; conduct of Self-Analysis Test for each

student, match every student to appropriate trade, attach every student to experts in such trade whether

available on or off campus and do periodic monitoring that will ensure that the goal of entrepreneurship for

all under-graduates of Nigerian tertiary institutions is achieved.

In addition, it is recommended that this Entreprenuership Education and Training should be taken a step

down to the secondary school level of education. This is to capture the group of young Nigerians whose

parents may not be able to afford the increasing cost of tertiary education in the country. By implication,

those leaving secondary schools would in the final analysis be gainfully self-employed if this

recommendation is accepted and implemented.

Secondly, government should be more serious with financial empowerment of Nigerians of all ages who

are ready to set up their own businesses. With lack of initial capital, nascent entrepreneurs with good skills

and expertise in various fields may find it difficult to launch into the world of business. What has been

discovered in the course of this study about government‟s lipservice to financial empowerment makes a

complete mockery of the scheme. Table 5.1 is from the records of National Directorate of Employment in

Oyo State between 1987 and 2010. From this table, the number of beneficiaries (107 in 23 years) has been



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too small. In addition the average loan given has been too small also, ranging from about N25, 000 in 1987

to 250,000 in 2010. A total of N14, 830,532 for a period of 23 years is a far cry from what is required.

Table 5.1 NDE OYO STATE

Information on SSE Programme From 1987 to 2010

S/n Scheme Target

Group

Year(s) of

disbursement

No

resettled

Total amount

disbursed

N

1. Graduate Employment

Scheme (State Pilot

Scheme)

Graduates

1987 – 1988

19

467,532

2. Mature People‟s Loan

Scheme

Retirees/Elderly

people

1987-1990

6

278,000

3. Motorcycle Loan Scheme Artisans/Schl.

Leavers

1994

10

880,000

4. Start Your Own Business

(SYOB) Scheme

Graduates

1999

3

400,000

5. NDE/NACRDB Loan

Scheme

Graduates/Matu

re People

2006

26

3,655,000

6. NDE/NACRDB Loan

Scheme

1. Start Your Own

Business (SYOB)

2. Basic Business

Training (BBT)

Graduates

Artisans

2009

6

4

900,000

1,000,000

7. Enterprise Creation

Scheme

Graduates &

Artisans

2008

Grad – 7

Art. – 5

1,750,000

500,000

8. NDE/NACRDB Graduates &

Artisans

2009

Grad – 6

Art. – 4

1,500,000

750,000

9. Enterprise Creation

Scheme

Graduates

2010

11

2,750,000

Total 107 14,830,532

Mean per beneficiary: 14,830,532 = N138,603

107

Mean per year: 14,830,532 = N644,806

23

NB: All loans under NDE/NACRDB collaboration were disbursed by NACRDB

Source: Complied by the author from Records of National Directorate of Employment Oyo State.

Thirdly, there was poor knowledge of the existence and activities of government agencies that have the

mandate to promote entrepreneurship in the country. As a result more needs to be done by government to

properly fund such agencies and make it compulsory for them to reach out to the Nigerian public.

Institutional based approaches may be relevant in this regard. Through periodic interactive sessions of

workshop and training, such agencies can showcase what they have to offer. This recommendation is not

meant for federal government agencies alone but for those at state government level set up to complement

what the government at the centre is doing. It is interesting to observe that whereas Oyo State government

has a Ministry of Establishment, Training and Poverty Alleviation almost all the sampled micro and small

business entrepreneurs did not know of its existence and activities.



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Fourthly, deliberate actions should be taken to assist micro and small business entrepreneurs in overcoming

the challenge of high cost of input and wares (articles sold by those in the distribution sub-sector).

Epileptic supply of electricity from the national grids has done a lot of damage to micro and small business

enterprises. Most entrepreneurs who require energy to be able to work do this at a very high cost. This in

turn has led to low patronage. Many entrepreneurs with this experience have completely abandoned their

enterprises for alternative sources of income, for which most had not been trained. A popular case in this

regard is the „Okada‟ transport business. As a result of high cost of input and other structural reasons,

Nigeria‟s textile industry is already in extinction, dispossessing several workers of their jobs and thereby

compounding the country‟s unemployment problem.

Of all challenges facing micro and small business entrepreneurship, low patronage is singled out. This is

because government can do something positive about it. The fifth recommendation therefore is that

government should be in the forefront of patronising micro and small business enterprises particularly with

regard to those sub-sectors where the enterprises produce what government needs. While patronage of the

individual enterprises may be good, cluster or network approach is strongly recommended. This is because

the small scale of production may not enable single enterprises to supply government adequately. With

government as a large market, long-run survival of the micro and small business may be guaranteed.

Finally government should harmonise the current existing multiple trade associations not just into few but

strong bodies. There are many advantages in doing this. First is that it will make it easy for government to

reach micro and small business entrepreneurs directly with policies targeted at strengthening them The

current situation where there are some shylock intermediaries between government and beneficiaries of its

policies would be avoided. Secondly, it will provide forum through which internal locus of the

entrepreneurs can be raised, thereby promoting the needed self-confidence for good business performance.

Thirdly, other strategies that can enhance profit maximisation (e.g. the need for and methods of having and

maintaining small household size) can be encouraged and in some cases demonstrated.

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Ahmad N. and Seymour R.G. (2008): “Defining Entrepreneurial Activity; Definitions Supporting

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